Overview
The RAG interview, answered. Six modules cover every RAG component (ingestion, preprocessing, chunking, embeddings, vector databases, retrieval, generation and evaluation), the frameworks and tools, production RAG systems, use-case designs for domains such as legal, healthcare and enterprise knowledge, and advanced RAG including self-correcting and agentic retrieval, closing with the follow-up questions interviewers ask next. Every answer is written in the first person with a concrete example, and many carry a diagram.
What you will learn
- Explain each RAG component and how its choices affect quality
- Choose chunking, embedding and vector database strategies
- Design retrieval, reranking and generation for grounded answers
- Evaluate a RAG system and find where it fails
- Take RAG to production with latency, cost and guardrails in mind
- Design RAG for legal, healthcare and enterprise use cases
- Discuss advanced patterns such as self-RAG, CRAG and agentic RAG
Included with the kit
- 60 written parts, yours for good
- 8h 33m of reading, measured not estimated
- Written for the intermediate level
- Every future revision included
- UPI, cards and netbanking
Prerequisites
- Working knowledge of LLMs and prompting
- Comfort reading Python
Curriculum
6 sections · 60 parts · 8h 33m01Module 1: RAG Components12 parts · 53 min
Understand every stage of a RAG pipeline, from ingestion and chunking to retrieval, generation, evaluation, and caching.
- RAG Components: Data Ingestion3 min
- RAG Components: Data Preprocessing3 min
- RAG Components: Chunking4 min
- RAG Components: Embeddings5 min
- RAG Components: Vector Database5 min
- RAG Components: Retrieval5 min
- RAG Components: Hybrid Search & Re-Ranking4 min
- RAG Components: Generation5 min
- RAG Components: Evaluation5 min
- RAG Components: Guardrails & Prompting5 min
- RAG Components: Query Expansion4 min
- Memory Management & Caching5 min
02Module 2: RAG Frameworks & Tools5 parts · 32 min
Choose and use LangChain, LlamaIndex, LangGraph, vector databases, and evaluation frameworks with confidence.
- LangChain8 min
- LlamaIndex7 min
- Vector Databases & Search Engines8 min
- Evaluation Frameworks4 min
- LangGraph5 min
03Module 3: Production RAG4 parts · 37 min
Run RAG systems at production scale with low latency, high throughput, and strong observability.
- Performance & Latency Optimization10 min
- Scalability & Throughput11 min
- Observability & Monitoring9 min
- Production Scenarios7 min
04Module 4: RAG Use Cases3 parts · 51 min
Design domain RAG systems end to end for legal, healthcare, and enterprise knowledge scenarios.
- Legal & Compliance RAG17 min
- Healthcare Knowledge RAG18 min
- Enterprise Internal Knowledge Base RAG16 min
05Module 5: Advanced RAG15 parts · 169 min
Go beyond basic RAG: advanced retrieval and chunking, multimodal, GraphRAG, agentic patterns, security, cost, MLOps, and specialised use cases.
- Advanced Retrieval Techniques16 min
- Advanced Chunking Strategies12 min
- Advanced RAG: Multimodal RAG13 min
- GraphRAG and Knowledge Graph Integration13 min
- Advanced RAG: Fine-tuning vs RAG10 min
- Advanced RAG: Multilingual RAG10 min
- Agentic RAG Patterns12 min
- RAG with Structured Data9 min
- RAG Security and Privacy13 min
- Cost Optimization in RAG11 min
- RAG Pipeline Testing and MLOps8 min
- Long Document RAG8 min
- Conversational RAG9 min
- RAG Deployment and MLOps11 min
- RAG for Specific Use Cases14 min
06Module 6: Follow-ups21 parts · 171 min
Handle the deeper follow-up questions interviewers ask after your first answer, topic by topic.
- Follow-ups: Data Ingestion7 min
- Follow-ups: Data Preprocessing7 min
- Follow-ups: Chunking8 min
- Follow-ups: Embeddings7 min
- Follow-ups: Vector Database8 min
- Follow-ups: Retrieval6 min
- Follow-ups: Hybrid Search & Re-ranking7 min
- Follow-ups: Generation7 min
- Follow-ups: Evaluation6 min
- Follow-ups: Guardrails & Prompting7 min
- Advanced Topics11 min
- Follow-ups: Query Expansion8 min
- Memory Management and Caching10 min
- Advanced Retrieval (Self-RAG, CRAG, Agentic)10 min
- Follow-ups: Multimodal RAG9 min
- GraphRAG9 min
- Follow-ups: Fine-tuning vs RAG8 min
- Follow-ups: Multilingual RAG9 min
- Cost Optimization8 min
- RAG Evaluation and Monitoring9 min
- Production Deployment and Incident Response10 min
Reviews
to review this kit once you have finished it.